SOTAVerified

Image Classification

Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.

Source: Metamorphic Testing for Object Detection Systems

Papers

Showing 21762200 of 10420 papers

TitleStatusHype
Multi-Label Image Classification via Knowledge Distillation from Weakly-Supervised DetectionCode1
A Less Biased Evaluation of Out-of-distribution Sample DetectorsCode1
Recalibrating Fully Convolutional Networks with Spatial and Channel 'Squeeze & Excitation' BlocksCode1
Automatically designing CNN architectures using genetic algorithm for image classificationCode1
MnasNet: Platform-Aware Neural Architecture Search for MobileCode1
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture DesignCode1
End-to-End Incremental LearningCode1
Invariant Information Clustering for Unsupervised Image Classification and SegmentationCode1
Age Estimation Using Expectation of Label Distribution LearningCode1
This Looks Like That: Deep Learning for Interpretable Image RecognitionCode1
DARTS: Differentiable Architecture SearchCode1
RISE: Randomized Input Sampling for Explanation of Black-box ModelsCode1
Manifold Mixup: Better Representations by Interpolating Hidden StatesCode1
Bayesian Model-Agnostic Meta-LearningCode1
Improving the Resolution of CNN Feature Maps Efficiently with MultisamplingCode1
Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy LabelsCode1
Wavelet Convolutional Neural NetworksCode1
Robust Classification with Convolutional Prototype LearningCode1
Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy LabelsCode1
HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentationCode1
BAGAN: Data Augmentation with Balancing GANCode1
Averaging Weights Leads to Wider Optima and Better GeneralizationCode1
Concurrent Spatial and Channel Squeeze & Excitation in Fully Convolutional NetworksCode1
Directional Statistics-based Deep Metric Learning for Image Classification and RetrievalCode1
Encoder-Decoder with Atrous Separable Convolution for Semantic Image SegmentationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified